IJMTES – MULTI-VIEW FOOD RECOGNITION USING MULTI-KERNEL BIASED MAXIMUM MARGIN ANALYSIS

Journal Title : International Journal of Modern Trends in Engineering and Science

Author’s Name : A Jayakumar | S Hemapriyaunnamed

Volume 03 Issue 06 2016

ISSN no:  2348-3121

Page no: 201-204

Abstract – Food recognition is a key factor for estimating the value of everyday food intakes. Food classification plays an important role in food recognition application. Recently, with the increase in unhealthy diets that will threaten people’s life due to the various risks like liver trouble, heart stroke and so on. In this project work we propose multi view food recognition using BMMA which is the mainstay of current image retrieval system. The food ingredients are detected through a combination of deformable part based model and a texture verification model. The food ingredients are classified based on the consideration like shape, color, size and texture. By using these features, better classification will be attained. The calorie Value of the food ingredient is evaluated from the PFID.

Keywords – food recognition, BMMA classification, calorie determination

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